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Every camera and sensing system we ship is used, every day, by hundreds of millions of people who simply expect it to work. Ensuring our systems are worthy of that expectation is this team's goal. We challenge products through the physical world to prove it, and to feed real-world evidence back into system design - measuring and analyzing the performance of multi-disciplinary optical sensing systems. This role is the analytical core of that work. You will define what we measure and why, mine large volumes of measurement data for the effect that actually matters, and take a question that has never been answered to a defensible answer. It is highly collaborative: you will work directly with module, optics, algorithm and system teams, and your conclusions will be the basis of their decisions. You will work alongside our lead system engineer as a peer, with problems allocated between you according to where the issue actually sits. We are looking for someone who genuinely enjoys digging into data until it gives up what it knows, and who wants to take that on with us.
Responsibilities
Own the characterization of system performance end to end - from risk and failure mode mapping through methodology definition, execution, analysis and reporting
Define metrics, testing & measurement methodology
Mine large data sets to separate isolate performance root causes
Correlate physical measurement to human perception - where the HW meets the user
Build the analysis capability the work requires - pipelines, tooling methods
Present and defend findings to module, optics, algorithm and system teams

Lead our operations in Israel, working closely with retailers to implement and scale our AI retail management platform.

Responsibilities
Lead our operational execution in Israel.
Work with retail chains to implement the platform in their stores.
Build and optimize internal processes for scale.
Collaborate with product and engineering on operational workflows.
Ensure smooth adoption and long-term usage for customers.

35,000 NIS/mo + bonuses.

Join our team in a pivotal role where you'll own the entire IP-level netlist generation and timing convergence journey from synthesis to sign-off.
You'll drive synthesis, UPF power intent, scan insertion, and external IP integration while architecting timing constraints for both standard and complex custom designs that ensure sign-off quality from day one.
Working at the intersection of multiple disciplines, you'll partner closely with RTL designers to deeply understand design intent and clock architecture, collaborate with CAD teams to shape and optimize cutting-edge flows, and team with Physical Design engineers to achieve flawless timing sign-off.
We're seeking an innovative thinker who brings fresh perspectives to timing analysis methodologies and proactively identifies and resolves timing challenges to eliminate pessimism and accelerate convergence, ultimately making their mark on next-generation chip design.

At our company, we work every single day to craft products that enrich peoples lives. Do you love working on challenges that no one has solved yet? Do you like changing the game? We have an opportunity for an exceptionally talented Design Verification Engineer. As a member of our dynamic group, you will have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of our customers every single day.

The position is relevant to all our sites: Herzliya, Haifa and Jerusalem

In this role, you'll participate in the architecture of next-generation PHY, conduct RTL implementation of the micro-architecture, and participate in clearly defining specification, testing, and verification of the PHY design.
Work in collaboration with CAD, PD teams to implement RTL design into GDS, run various design verification flows and provide guidelines to other designers, and participate in establishing CAD and design methodologies for correct-by-construction designs

We are looking for a DevOps Engineer to own and scale the infrastructure behind our AI systems.

What you'll do
Own cluster reliability, availability, monitoring, alerting, capacity planning, and incident response.

Configure, maintain, and troubleshoot GPU servers, networking equipment, switches, InfiniBand fabrics, storage, and related infrastructure.

Deploy, maintain, and improve infrastructure around Slurm, Kubernetes, and GPU workload orchestration.

Manage and improve our cloud environment, including compute, networking, storage, IAM, security groups, cost visibility, and production infrastructure.

Build, maintain, and improve CI/CD pipelines.

Work closely with engineers to understand infrastructure bottlenecks and improve development, training, inference, and deployment velocity.

Contribute to security best practices across cloud, network, CI/CD, access control, secrets management, and production systems.

We are looking for a Deep Learning Engineer to help design, implement, optimize, and scale the training and inference systems behind our models.

What you'll do
Collaborate with cross-functional teams to bring research breakthroughs into production environments.

Build tools, abstractions, and infrastructure that make model training, evaluation, and deployment faster and more reliable.

Analyze and overcome performance and scalability challenges in large-scale distributed training.

Debug complex issues across the full ML stack: data loading, model code, distributed execution, GPU utilization, memory usage, networking, checkpointing, and serving.

Work with modern training and inference frameworks such as Megatron, TorchTitan, PyTorch, and vLLM.

We are seeking talented, creative and disciplined engineers to join the best-in-class team that plays a significant part in the development of new silicon for our eco-systems by engaging in a dynamic, highly collaborative environment with the focus on the following goals.

Deep understanding of components/modules within wireless communication systems and the corresponding calibration and impairment reduction techniques - Develop methods/algorithms to alleviate hardware induced impairments by calibration, cancellation and other applicable techniques - PHY firmware architecture and design, including calibrations, real-time processing flows, collaboration with RF hardware, microcode, and MAC layer.

Develop highly efficient designs delivering outstanding performance, optimizing power and memory footprints while meeting hard-realtime latency requirements.

Debug real-time systems with limited visibility, working hands-on with development boards and lab equipment.

Collaborate with Radio, MAC, and Systems engineering teams to architect, define and implement innovative algorithms, calibrations, and protocols.

Support pre-silicon validation efforts, including simulation, emulation, and FPGA prototyping.

Develop SoC test and calibration capabilities for chip, module, and product factories.

Support post-silicon bringup, validation, performance characterization, system integration and debugging. - Repeatedly measure and optimize results using various test harnesses - Automate calibration and verification processes

We are looking for a Product Engineer to own and ship the products that put this capability in the hands of engineers, data scientists, and researchers.

What you'll do
Own product features end-to-end: scope, build, ship, measure, and iterate - across CLI, IDE integrations, web surfaces, and the AI pipeline behind them.

Talk directly to users - engineers, data scientists, ML practitioners - and let their feedback shape what you build next.

Define what AI-powered code optimization and verification feels like as a developer experience: the interaction model, the feedback loops, the trust signals. There is no established playbook; you will create the conventions.

Craft interfaces that feel fast, focused, and effortless for technical users who have zero patience for friction.

Collaborate with researchers to translate model breakthroughs into polished, reliable tooling that developers can depend on in production.

Build evaluation infrastructure and product metrics that measure whether the tools are actually getting better.

Work directly with the founding team on product strategy and roadmap.

We are looking for someone with strong fundamentals, algorithmic problem solving capabilities, hands-on engineering skills, a collaborative mindset, and a desire for continuous learning. We value people who are comfortable moving between code, systems, algorithms, and problem domains.

What you'll do
Write production-grade code powering frontier AI systems.

Work on performance, scalability, and reliability of distributed systems.

Collaborate with researchers and engineers to turn ideas into systems that run.

Improve tooling, infrastructure, and developer workflows.

As a member of our Physical Design team in this highly visible role, you will directly own implementation and verification of design partition(s) / IPs (netlist to delivery of our final GDS) for a highly complex SoC utilizing state of the art process technology.
* Implementation - Block level PnR, floor-planning, clock, power planning and distribution.
* Verification and Analysis - Static Timing closure using commercial tools, Physical Verification as well as Electrical/Power Analysis (EM / IR-Drop / Xtalk / noise )